Both trace agents, run offline and online evals, route traces to human reviewers and version prompts. HoneyHive is built on OpenTelemetry and traces a wide range of agents, including coding agents and enterprise agent platforms; Maxim AI adds text and voice simulation, an open-source gateway and self-serve paid plans. How you want to buy beyond the free tier often decides it.[1][4]
HoneyHive and Maxim AI are both hosted agent evaluation and observability platforms from small, independent companies; the main difference is that Maxim AI sells self-serve paid plans and adds voice simulation and a gateway, while HoneyHive has a free tier and then a sales-led Enterprise plan, with broad tracing for coding agents and enterprise agent platforms. Neither evaluation platform blocks live actions; Maxim AI can through its Bifrost Enterprise gateway.
| Decision factor | HoneyHive | Maxim AI |
|---|---|---|
| Ownership | Independent; $7.4M total funding announced April 2025 | Independent; $3M seed led by Elevation Capital in 2024 |
| Buying | Free tier, then Enterprise via sales; no self-serve paid plan | Free tier, then self-serve per-seat plans, then Enterprise |
| Tracing breadth | Agent frameworks plus Claude Code, Codex CLI, Devin, Agentforce and Agent Bricks | Agent frameworks plus voice stacks such as LiveKit and ElevenLabs |
| Simulation | Experiments on datasets with CI gating | Multi-turn text and voice simulation, plus test runs |
| SDKs | Full tracing SDK in Python; TypeScript is a REST client (OTLP otherwise) | Python, JavaScript/TypeScript, Go and Java |
| Self-hosting | Enterprise; fully self-hosted or hybrid, documented on AWS | Enterprise in-VPC on AWS, GCP or Azure |
| Runtime blocking | None documented | Through Bifrost Enterprise guardrails |
| Free tier | 10,000 events a month, 30-day retention, up to 5 users | 10k logs a month, 3-day retention, up to 3 seats |
| Capability | HoneyHive | Maxim AI | Prefactor |
|---|---|---|---|
| Observe | |||
| LLM call tracing | ✓ | ✓ | ✓ |
| Multi-step agent tracing (tool calls, nested spans) | ✓ | ✓ | ✓ |
| Cost tracking | ✓ | ✓ | ✓ |
| OpenTelemetry support | ✓ | ✓ | ✓ |
| Evaluate | |||
| Offline evals (datasets, experiments) | ✓ | ✓ | ✓ |
| Online evals on production traffic | ✓ | ✓ | ✓ |
| LLM-as-a-judge scoring | ✓ | ✓ | ✓ |
| Code-based evaluators | ✓ | ✓ | ✓ |
| Human review and annotation | ✓ | ✓ | ✓ |
| Prompt versioning and playground | ✓ | ✓ | — |
| Act on findings | |||
| Runtime controls on live agent actions | — | ✓ | ✓ |
| Gateway or proxy in the request path | — | ✓ | — |
| Licence and deployment | |||
| Open source | Partial | Partial | Partial |
| Self-hosting | ✓ | ✓ | Partial |
This is the most practical difference. HoneyHive's Developer tier is free with no card for 10,000 events a month, 30-day retention and up to 5 users. Above that there is no published self-serve plan; Enterprise is quote-based and covers custom limits, SSO, data residency and self-hosting. Maxim AI's Developer tier is free for up to 3 seats and 10k logs with 3-day retention, and two self-serve plans sit above it before Enterprise.
For a team that wants to grow usage gradually on a card, Maxim AI is the simpler path. For a team that will go through procurement anyway, HoneyHive's longer free retention and higher user limit make for a more useful evaluation period.
Both companies are small and seed-funded. HoneyHive's last announced funding was $7.4M in total, in April 2025, and third-party directories put its staff at roughly 18 to 19. Maxim AI raised a $3M seed in 2024. HoneyHive's changelog shows releases in most months of 2026; Maxim AI's public changelog shows no dated 2026 entries, and its newest monthly update post covers December 2025.
HoneyHive is built on OpenTelemetry and reads OTel GenAI, OpenLLMetry and OpenInference conventions. Beyond the usual agent frameworks it traces coding agents such as Claude Code, Codex CLI and Devin, with usage and spend analysis, and since August 2026 Salesforce Agentforce and Databricks Agent Bricks. It shows runs as agent graphs, trajectories, threads, timelines and, since September 2026, a conversation view. In June 2026 it was named the observability partner in Microsoft's ASSERT announcement.
Maxim AI's strength is before release: multi-turn simulation of text and voice agents, test runs for prompts, no-code agents and agents behind an HTTP endpoint, and simulation for AWS Bedrock Agents and Glean agents. It also ingests OTLP over HTTP and lists SDKs for Python, JavaScript and TypeScript, Go and Java. HoneyHive's full tracing SDK is Python; its TypeScript package is a REST client, so other languages use OTLP.
Evaluation features are close. HoneyHive runs LLM evaluators with Jinja2 templates and versioning, server-side Python evaluators and human evaluators; its online evals score sampled production traces, with default sampling lowered to 10% in May 2026, and experiments gate CI through GitHub Actions. Maxim AI offers pre-built, LLM, code and API-based evaluators, scores production logs at session, trace and node level with filter- and rate-based sampling, and alerts to Slack and PagerDuty. Both version and deploy prompts, with a playground.
Both self-host only on Enterprise. HoneyHive offers fully self-hosted, with control and data plane in your environment, or hybrid, with a self-hosted data plane and HoneyHive's hosted control plane; its documentation covers AWS only. Maxim AI deploys in your VPC on AWS, GCP or Azure, fully isolated or as a data plane only.
HoneyHive documents no blocking, guardrails or approvals on live agent actions. Its Policies feature sets evaluation and monitoring standards across an organisation, and in the Microsoft ASSERT partnership it is the observability layer while the specification handles enforcement. Maxim AI's evaluation platform also observes, but its Bifrost gateway's guardrails can block, redact or transform inputs, outputs and MCP tool-call content, as a Bifrost Enterprise feature.
As of 20 October 2026, HoneyHive lists a free Developer tier and a quote-based Enterprise plan, with nothing in between. Maxim AI's Professional plan is $29 per seat a month with 100k logs and 7-day retention, and Business is $49 per seat a month with 500k logs and 30-day retention, with overage at $1 per 10k logs. Enterprise on both is custom. Compare HoneyHive's pricing and Maxim AI's pricing for your expected volume and team size. HoneyHive's free tier counts events while Maxim AI's counts logs, so check how each records a single agent run before comparing the allowances.
We sell the layer this section describes. Read it with that in mind.
Stated plainly, since Prefactor publishes this page: Prefactor is an agent evaluation platform that scores each step of a run and acts on what it finds through runtime policies, approval holds and a kill switch scoped to a run, an agent or a team. HoneyHive observes and scores without acting during a run; Maxim AI can block content through Bifrost Enterprise guardrails but documents no approval holds. Prefactor has no prompt playground or prompt registry and its platform is hosted, so if prompt iteration or coding-agent tracing is the priority, Maxim AI or HoneyHive is the better pick. See the full comparison of 15 platforms.
Reviewed against public product and documentation pages on October 20, 2026. If a vendor has changed a feature, product name, or positioning since then, send a correction and we will update it. Numbered source links in the page body point to the ordered sources below.
Prefactor scores each step of every agent run and can hold or stop an action when a score says it should not happen. Start on the free tier: 5,000 spans a month, no credit card required.
Prefactor helps teams observe, evaluate, and improve their AI agents in production, across every framework and provider.